Tag Archives: retail

Amazon opened its first physical bookstore in Seattle on Nov 2. This is not the first time a pure play online retailer has opened a bricks-and-mortar store. Warby Parker and Bonobos have done it before. But Amazon is the 800 pound Gorilla of online retailing and has steadfastly resisted going offline thus far.

So why did Amazon bite the bullet and open its physical store? Several factors may explain this development. First, despite the phenomenal growth in online retail, a substantial chunk of sales is still offline. People still love to go to physical bookstores and browse books. Second, it could just be an experiment. Amazon may want to test the waters offline given that many pure play online retailers have been doing it before. Third, it could be firing a salvo at Walmart, the world’s biggest offline retailer and its biggest rival, which has made tremendous strides in online retail. Fourth, it may be changing the way brick-and-mortar stores designed. It has designed its physical store with data collected from its online store based on customer reviews and sales measures. Finally, sales of e-books may be leveling or even falling.

Whatever the reason, when the world’s most valuable retailer like Amazon enters the physical turf, it promises to elevate omnichannel retailing to a new level. Let the games begin!

An important part of the rapidly growing shopper marketing practice is cross-category retail management. In managing two related product categories,
retailers face some important questions: which category should be stocked more? How close to each other should they be stocked in the store (aisle adjacency)? which category should be promoted more often? and when should the two categories be sold as a bundle? To address these questions, we examine how purchases of related product and sub-product categories influence one another, and how the relative aisle locations of two related product categories influence their respective purchases. We consider both extrinsic (aisle location based) and intrinsic (affinity based) cross-category effects. Using aggregate store-level data together with store descriptor and store shopper demographic data, we estimate a simultaneous system of models for two related product categories, soft drinks and salty snacks. We also estimate a system of salty snack sub-category purchase models. We find that both extrinsic and intrinsic cross-category effects are asymmetric, that is, different categories and sub-categories have different effects on one another. We discuss the theoretical and managerial implications of these findings.

Karen Katz, CEO and President, Neiman Marcus answered my questions before an auditorium full of students, faculty and staff at the Mays Business School, Texas A&M on April 2, 2014. Karen Katz started as an assistant buyer with the company took over as the CEO in 2010. She is continuously engaged in delivering customized experience to Neiman Marcus’ luxury customers. I had a chance to moderate her talk. She spoke on a range of topics. Below is a video link to the interview.

How does the monetary value of customer purchases vary by customer preference for purchase channels (e.g., traditional, electronic, multichannel) and product category? The authors develop a conceptual model and hypotheses on the moderating effects of two key product category characteristics—the utilitarian versus hedonic nature of the product category and perceived risk—on the channel preference–monetary value relationship. They test the hypotheses on a unique large-scale, empirically generalizable data set in the retailing context. Contrary to conventional wisdom that all multichannel customers are more valuable than single-channel customers, the results show that multichannel customers are the most valuable segment only for hedonic product categories. The findings reveal that traditional channel customers of low-risk categories provide higher monetary value than other customers. Moreover, for utilitarian product categories perceived as high (low) risk, web-only (catalog- or store-only) shoppers constitute the most valuable segment. The findings offer managers guidelines for targeting and migrating different types of customers for different product categories through different channels.

The objectives of this course are to enable the participants develop a deep understanding of retail economics, shopper marketing, solution selling, total promotions, cross-selling, and channel partnering. The key topics covered also include retail environment, trends in and future of retailing, retail buying behavior, total promotions, and communicating the value proposition to channel partners.

This course is designed to give you a good understanding of how marketers develop an understanding of customer value and use that understanding to make sound marketing decisions. The focus will be on understanding the basic concepts and application of marketing for customer value in the form of case analysis, discussion of real-world examples, and development and presentation of marketing strategies. The course will emphasize the following key elements: (1) Customer Analysis: Issues of focal concern include analysis of customer value, segmentation analysis, target market selection, and value proposition or product positioning, and customer satisfaction; and (2) Marketing Decision Making Process: This process enables the marketing manager to systematically organize the relevant issues to make appropriate marketing strategy decisions based on analysis of the market situation. The major emphasis of this process will be on application of the relevant marketing tools of analysis to the marketing decisions. Financial analysis of marketing decisions will be stressed.

This article was published in Marketing Science, 23 (Winter 2004), 28-49.

This paper empirically investigates the determinants of retailers’ pricing decisions with a focus on competitor factors. We classify the different types of pricing strategies based on four underlying dimensions. These dimensions are price consistency, price-promotion intensity, price-promotion coordination, and relative brand price. We develop and estimate a simultaneous equation model of how each of the underlying dimensions of retailers’ pricing strategies is influenced by variables representing the market, chain, store, category, brand, customer and competition. Our empirical analysis is based on optical scanner data that describe 1364 brand-store combinations from six categories of consumer packaged goods in fiveU.S.markets over a two year time period. The four underlying pricing dimensions are statistically related to: (1) competitor price and deal frequency (competitor factors), (2) storability and necessity (category factors), (3) chain positioning and size (chain factors), (4) store size and assortment (store factors), (5) brand preference and advertising (brand factors), and (6) own price and deal elasticities (customer factors). Competitor factors explain the most variance in retailer pricing strategy, followed by category and chain factors. Only in the cases of price-promotion coordination and relative brand price, do category and chain factors explain much variance in retailer pricing. Store, brand and customer factors capture an insignificant proportion of explained variance in retailer pricing. These findings are useful to retailers in profiling alternative pricing strategies. They can also help manufacturers make informed decisions about the levels of marketing support spending for their brands that are appropriate for different retailers. We outline the managerial implications based on the results.